Senior Software Engineer, Machine Learning
Z
ZipRecruiterOnline Employment Marketplace
Most US-based positions can also be performed remotelyFull-TimeSenior
Salary140000 - 225000 USD per year
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Job Details
- Experience
- 3+ year of professional software development experience with a focus in machine learning
- Required Skills
- Machine LearningNLTKPyTorchAlgorithmsData StructuresTensorflowscikit-learnNLP
Requirements
- 3+ year of professional software development experience with a focus in machine learning
- Deep experience in machine learning algorithms, techniques, and best practices
- Comprehensive computer science fundamentals in coding, object-oriented programming, data structures, and algorithms
- 5+ year of professional software development experience with a focus in machine learning
- BS/MS/PhD in Mathematics, Computer Science, Physics, related technical field or equivalent practical experience
- Strong knowledge of machine learning algorithms (e.g., linear regression, SVM, decision trees, neural networks, clustering, etc.) and best practices
- Experience with machine learning algorithms and frameworks, such as TensorFlow, PyTorch, or scikit-learn
- Experience with deep learning architectures and techniques, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM), and Generative Adversarial Networks (GANs)
- Background with NLP techniques and tools, such as tokenization, stemming, lemmatization, sentiment analysis, and named entity recognition, and libraries like NLTK, SpaCy, or BERT
Responsibilities
- Design, develop, and maintain machine learning models and algorithms to solve complex business problems
- Identify patterns, trends, and anomalies in the data, and visualize insights using appropriate tools
- Assess the performance of machine learning models using appropriate metrics, validation techniques, and testing datasets
- Discover opportunities to optimize models by fine-tuning hyperparameters, feature selection, or employing regularization techniques to improve accuracy, performance, and scalability
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